Llama 3.1 405B Deployment on Vertex AI

This provides a technical guide for deploying Meta's latest open LLM, the Llama 3.1 405B model, on Google Cloud Vertex AI. It focuses in particular on running the memory-efficient FP8 quantized version on A3 nodes based on NVIDIA H100 GPUs.

Key points are as follows:

• Deployment methods: Supports both programmatic deployment using Hugging Face's dedicated Deep Learning Containers (DLCs) and Text Generation Inference (TGI), as well as no-code deployment via Vertex Model Garden.
• Hardware requirements: Details the VRAM requirements according to model size and precision (FP16, FP8, INT4). For the 405B model, using FP8 precision requires approximately 405GB of VRAM.
• Workflow: Explains the entire process step by step, from Google Cloud environment setup to model registration, running online predictions, and cleaning up resources.